DarkTrace > Case Studies > Enhancing Security Infrastructure with AI: A Case Study of EV Group

Enhancing Security Infrastructure with AI: A Case Study of EV Group

Technology Category

Application Infrastructure & Middleware - Event-Driven Application
Platform as a Service (PaaS) - Device Management Platforms

Applicable Industries

Equipment & Machinery
National Security & Defense

Use Cases

Autonomous Transport Systems
Tamper Detection

The Customer

EV Group

About The Customer

EV Group is a leading semiconductor manufacturer with a complex digital infrastructure. The company's security team was seeking to improve their security posture by gaining packet-level visibility and reducing the time to response for security incidents. They were relying on log-based SIEM technology, which provided an overview of the digital estate but lacked the necessary packet-level insight. The team aimed to minimize the time between an event happening and it being acknowledged, ideally less than 10 minutes. They trialled Darktrace alongside other tools, deciding on Darktrace's Self-Learning AI primarily because of the accuracy of its detections.

The Challenge

EV Group, a leading semiconductor manufacturer, was grappling with the complexity of its digital infrastructure. The company's security team was seeking packet-level visibility to improve their security posture. They were relying on log-based SIEM technology, which provided an overview of the digital estate but lacked packet-level insight at the network traffic layer. This meant that security incidents were not being recognized and controlled quickly enough. The primary goal was to minimize the time between an event happening and it being acknowledged, ideally less than 10 minutes. The team trialled Darktrace alongside other tools, deciding on Darktrace's Self-Learning AI primarily because of the accuracy of its detections.

The Solution

EV Group implemented Darktrace's Self-Learning AI to enhance their security infrastructure. Darktrace's AI technology learns the 'patterns of life' for every user and device in the organization and spots subtle deviations indicative of a threat. This technology provided packet-level insight and accurate detections, reducing the time to response for security incidents. Darktrace also revealed configuration errors that could represent a backdoor into EV Group's digital estate, helping the security team become more strategic in cleaning up their digital infrastructure. The team set the technology to surface only the events that have occurred in the last 24 hours, and every anomaly is looked at to ensure that the Darktrace dashboard is clean at the end of every day. To ensure round-the-clock security, EV Group added Autonomous Response to their security stack, which takes targeted and proportionate action against threats whenever they occur.

Operational Impact

The implementation of Darktrace's Self-Learning AI has significantly improved EV Group's security infrastructure. The AI technology provides packet-level insight and accurate detections, enabling the security team to recognize and control security incidents more quickly. The technology also reveals configuration errors that could represent potential backdoors into the digital estate, helping the team to strategically clean up their infrastructure. The addition of Autonomous Response to the security stack ensures round-the-clock security, taking targeted and proportionate action against threats whenever they occur. The team's confidence in the technology is so high that they assess every anomaly surfaced by Darktrace, ensuring a clean dashboard at the end of every day.

Quantitative Benefit